Incorporating Computer Vision and Machine Learning for Lane and Curve Detection in Vehicle Mobility

This research presents an approach to single-lane road detection using computer vision techniques, facilitated by a compact camera module. The system captures real-time footage, processed by a Raspberry Pi. The study showcases a prototype of an autonomous vehicle constructed for multiple applications such as transportation and deliveries. The model integrates a combination of pixel summation and deep learning approaches, as well as advanced algorithms, to accurately detect lanes, curves, and estimate the vehicle’s lateral offset relative to the lane center. The overarching aim is to maintain the vehicle’s optimal position on the road, ensuring safety and precision. This approach has the potential for transforming transportation, particularly for people with mobility issues.